Home > Research > Researchers > Professor Christopher Nemeth > Publications

Research

Professor Christopher Nemeth

Professor of Probabilistic Machine Learning, Research Student

1 - 25 out of 52Page size: 25
RSS feed of this list
  1. Published

    Stochastic Gradient MCMC for Nonlinear State Space Models

    Aicher, C., Putcha, S., Nemeth, C., Fearnhead, P. & Fox, E. B., 29/01/2019, In: arXiv.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  2. Published

    Stochastic Gradient MCMC for Nonlinear State Space Models*

    Aicher, C., Putcha, S., Nemeth, C., Fearnhead, P. & Fox, E. B., 31/03/2025, In: Bayesian Analysis. 20, 1, p. 1385-1407 23 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Published

    Control variates for stochastic gradient MCMC

    Baker, J., Fearnhead, P., Fox, E. B. & Nemeth, C., 1/05/2019, In: Statistics and Computing. 29, 3, p. 599-615 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Published

    sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo

    Baker, J., Fearnhead, P., Fox, E. B. & Nemeth, C. J., 31/10/2019, In: Journal of Statistical Software. 91, 3, p. 1-27 27 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. Published

    Large-Scale Stochastic Sampling from the Probability Simplex

    Baker, J., Fearnhead, P., Fox, E. B. & Nemeth, C., 3/12/2018, p. 6722-6732 . 11 p.

    Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

  6. Published

    Telling the Researcher STOR-i With Data Science: Elsevier data scientists are working with Lancaster University researchers to advance our understanding of researcher behaviors

    Bolt, G. (Other), Muncey, H., Lunagomez Coria, S. (Other) & Nemeth, C. (Other), 2020

    Research output: Exhibits, objects and web-based outputs › Web publication/site

  7. Published

    Modelling Populations of Interaction Networks via Distance Metrics

    Bolt, G., Lunagómez, S. & Nemeth, C., 20/06/2022.

    Research output: Working paper › Preprint

  8. Published

    Distances for Comparing Multisets and Sequences

    Bolt, G., Lunagómez, S. & Nemeth, C., 17/06/2022, Arxiv.

    Research output: Working paper › Preprint

  9. Published

    Robust Bayesian Nonparametric Variable Selection for Linear Regression

    Cabezas, A., Battiston, M. & Nemeth, C., 23/05/2021.

    Research output: Working paper › Preprint

  10. Published

    Transport Elliptical Slice Sampling

    Cabezas, A. & Nemeth, C., 25/04/2023, In: Proceedings of Machine Learning Research. 206, p. 3664-3676 13 p.

    Research output: Contribution to Journal/Magazine › Conference article › peer-review

  11. Published

    Robust Bayesian nonparametric variable selection for linear regression

    Cabezas, A., Battiston, M. & Nemeth, C., 27/05/2024, In: Stat. 13, 2, e696.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  12. Forthcoming

    Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows

    Cabezas Gonzalez, A., Sharrock, L. & Nemeth, C., 25/09/2024, (Accepted/In press) In: Advances in Neural Information Processing Systems.

    Research output: Contribution to Journal/Magazine › Conference article › peer-review

  13. Published

    SGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithms

    Coullon, J. & Nemeth, C., 18/04/2022, In: Journal of Open Source Software. 7, 72, 2 p., 4113.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  14. Published

    Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC

    Coullon, J., South, L. & Nemeth, C., 27/05/2021, Arxiv.

    Research output: Working paper › Preprint

  15. Published

    Efficient and generalizable tuning strategies for stochastic gradient MCMC

    Coullon, J., South, L. & Nemeth, C., 30/06/2023, In: Statistics and Computing. 33, 3, 66.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  16. Forthcoming

    Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds

    Dodd, D., Sharrock, L. & Nemeth, C., 1/05/2024, (Accepted/In press) In: Proceedings of Machine Learning Research.

    Research output: Contribution to Journal/Magazine › Conference article › peer-review

  17. Published

    GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language

    Fairbrother, J., Nemeth, C., Pinder, T., Rischard, M. & Brea, J., 30/04/2022, In: Journal of Statistical Software. 102, 1, p. 1-36 36 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  18. Published

    Scalable Monte Carlo for Bayesian Learning

    Fearnhead, P., Nemeth, C., Oates, C. J. & Sherlock, C., 5/05/2025, Cambridge: Cambridge University Press. ( Institute of Mathematical Statistics Monographs)

    Research output: Book/Report/Proceedings › Book

  19. E-pub ahead of print

    A changepoint approach to modelling non-stationary soil moisture dynamics

    Gong, M., Killick, R., Nemeth, C. & Quinton, J., 29/01/2025, (E-pub ahead of print) In: Journal of the Royal Statistical Society. Series C: Applied Statistics. 74, 3, p. 866-883 18 p., qlaf004.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  20. Published

    Bearings-Only Tracking with Particle Filtering for Joint Parameter Learning and State Estimation

    Nemeth, C., Fearnhead, P., Mihaylova, L. & Vorley, D., 7/07/2012, Information Fusion (FUSION), 2012 15th International Conference on. IEEE, p. 824-831 8 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  21. Published

    Particle Learning Methods for State and Parameter Estimation

    Nemeth, C., Fearnhead, P., Mihaylova, L. & Vorley, D., 15/05/2012, Data Fusion & Target Tracking Conference (DF&TT 2012): Algorithms & Applications, 9th IET. 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  22. Unpublished

    Particle Metropolis adjusted Langevin algorithms for state space models

    Nemeth, C. & Fearnhead, P., 4/02/2014, (Unpublished) In: arxiv.org.

    Research output: Contribution to Journal/Magazine › Journal article

  23. Published

    Sequential Monte Carlo methods for state and parameter estimation in abruptly changing environments

    Nemeth, C., Fearnhead, P. & Mihaylova, L., 1/03/2014, In: IEEE Transactions on Signal Processing. 62, 5, p. 1245-1255 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  24. Published

    Parameter estimation for state space models using sequential Monte Carlo algorithms

    Nemeth, C., 2014, Lancaster University. 204 p.

    Research output: Thesis › Doctoral Thesis

  25. Published

    Particle Metropolis-adjusted Langevin algorithms

    Nemeth, C., Sherlock, C. & Fearnhead, P., 09/2016, In: Biometrika. 103, 3, p. 701-717 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

Previous 1 2 3 Next

Back to top